Department of Computer Engineering
Research Topic: Ionospheric model development for Indian region using IRNSS satellite data
Research Area: Data mining and artificial neural network
Abstract: Ionosphere plays vital role in the navigation positional accuracy determination, in robust satellite communication. Ionosphere consists of different layers depending on the altitude and its electron density in the layer. Literature cites different ionospheric models predicting the total electron density with spatial and temporal resolutions. These models are mostly using GPS satellite data. The need is felt that there is a requirement of developing ionospheric models for low latitudes of Indian region with different time duration. This research proposal is intended for developing a model to predict 3D tomography of total electron density for entire Indian region. This model is proposed to be developed using IRNSS satellite data collected from RNSS Range and Integrity Monitoring Stations (IRIMS) and various reference receivers spread over entire Indian main land and islands. This data is acquired daily for every second and sent to centralized place. The handling of this enormous data is proposed to use data mining algorithms, artificial neural network techniques for prediction.
Research Topic: Weather cloud phase detection using remote sensing data
Research Area: Machine learning
Abstract: Weather cloud consist of a visible mass of tiny dew drops, ice covered crystals, or other particles suspended in the atmosphere. Clouds cover approximately 60% of the Earth’s surface and they strongly influence weather and climate. Clouds significantly impact radiative heating rates, latent heating rates, moisture transport and uncertainty in climate models and predictions of atmospheric effects on remote sensing measurements. The microphysical properties, spatial coverage, and location of clouds dictate the effect of clouds on the earth– atmosphere system. The literature survey shows that lots of work has been done in the field of cloud detection and cloud classification. But still there is need to explore more in the area of cloud phase detection. There are four phase categories: liquid water cloud top, with temperatures warmer than 273 K or colder than 273 K (i.e., super cooled), mixed-phase (liquid water and ice) clouds and glaciated (ice) clouds. Appropriate phase detection is a critical step for remote sensing retrievals of cloud properties such as optical thickness (COT), effective particle radius (CER), and water path. Proposed study intend to develop hybrid method which can work on big data of satellite image. It is proposed to consider the physical understanding of the environment, atmospheric parameters and machine learning techniques to overcome constraints and drawbacks of existing algorithms.
Research Topic: Mangrove parameters estimation of selected region using remote sensing data
Research Area: Big data analysis and machine learning
Abstract: Preliminary literature study indicates that satellite remote sensing data is not yet applied to estimate Mangrove parameters of selected region. The proposed study aims to estimate mangrove features using multi-date, multi-polarization SAR (Synthetic Aperture Radar) data, multi band and hyperspectral band optical data. This data may be used for species discrimination, estimation of mangrove height, biomass, detection of mudflat type for mangrove plantation and carbon credit precise differentiation between mangrove and non-mangrove vegetation and canopy texture based assessment for mangrove health. Basically multiple images of SAR and multispectral, hyperspectral images along with ground truth will be used as input for model formation. After data preprocessing based on type of parameter and complexity of the relationship of parameter, correlation / multilinear regression /machine learning technique will be applied. Individual and combined models will be built and will be assessed for accuracy. Model will be more refined using multi-date data over study area.
Research Topic: Big data analysis for Gujarat state coastal ecosystem study
Research Area: Big data analysis and machine learning
Abstract: Large proportion of human population of the State is dependent on these coastal ecosystems for their livelihood. They are very important source of various non-timber forest products for coastal communities such as fire wood, honey, gum etc. Number of marine animals such as whale shark, and sea turtles are residents of the Gujarat coast. Therefore, conservation and protection of these ecosystems is very important for the sustainable growth and development of the State. Preliminary literature study indicates that there is huge scope of satellite remote sensing data application in the area of forest ecology. It is proposed to carry out Big data analysis on data such as multiple images of SAR (Synthetic Aperture Radar), multispectral, hyperspectral images for different applications like mangrove characterization, rainfall prediction, forest fire study. After data preprocessing based on type of parameter and complexity of the relationship of parameter, correlation / multilinear regression /machine learning technique will be applied. Individual and combined models will be built and will be assessed for accuracy. Model will be more refined using multi-date data over study area.
Research Topic: Efficient enhancement of Data Security in the Cloud Environment.
Research Area: Big Data Security in Cloud Environment
Abstract: The digitization, atomization and significant growth in the IT Industry during the span of the last decade has enabled cloud computing to emerge as the most popular buzzword. Furthermore, the cutting edge technologies like the Internet of things, Machine learning also require cloud services to cater to the data storage and processing needs. As per the case study conducted by Cisco, more than 50,000 lakhs devices are going to get connected with the internet in the near future. The abundance of devices connected to the internet may significantly increase the cloud market as a much larger cloud task is going to deploy in the near future. Hence, it is expected that in India only the cloud market is going to reach the new horizons. Clearly, the optimized and secure usage of cloud service is going to be essential in the near future.
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